Analysis of capture–recapture models with individual covariates using data augmentation

J. Andrew Royle

doi:10.1111/j.1541-0420.2008.01038.x

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Analysis of capture–recapture models with individual covariates using data augmentation

J. Andrew Royle

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Abstract

I consider the analysis of capture–recapture models with individual covariates that influence detection probability. Bayesian analysis of the joint likelihood is carried out using a flexible data augmentation scheme that facilitates analysis by Markov chain Monte Carlo methods, and a simple and straightforward implementation in freely available software. This approach is applied to a study of meadow voles ( Microtus pennsylvanicus ) in which auxiliary data on a continuous covariate (body mass) are recorded, and it is thought that detection probability is related to body mass. In a second example, the model is applied to an aerial waterfowl survey in which a double‐observer protocol is used. The fundamental unit of observation is the cluster of individual birds, and the size of the cluster (a discrete covariate) is used as a covariate on detection probability.

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BibTeX RIS

J. Andrew Royle. 2009-03-17. Analysis of capture–recapture models with individual covariates using data augmentation. https://doi.org/10.1111/j.1541-0420.2008.01038.x

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